Feasibility of Innovative Smart Mobility Solutions for Vaasa – A Case Study of EU Horizon 2020 IRIS Project

Kokoteksti

(1)Tomi Paalosmaa. Master’s Thesis: Feasibility of Innova6ve Smart Mobility Solu6ons for Vaasa – A Case Study of EU Horizon 2020 IRIS Project. School of Technology Master’s thesis in Smart Energy Programme. Vaasa 2021.

(2) 2. UNIVERSITY OF VAASA School of Technology Author: Title of the Thesis: Degree: Programme: Supervisor: Year: Pages:. Tomi Paalosmaa Feasibility of InnovaBve Smart Mobility SoluBons for Vaasa – A Case Study of EU Horizon 2020 IRIS Project Master’s in Technology Smart Energy Hannu Laaksonen & Miadreza Shafiekhah 2020 124. ABSTRACT: The primary purpose of this thesis is to examine the innovaBve smart mobility, and second life baRery soluBons, represented in the City of Vaasa’s Horizon 2020 IRIS Smart CiBes ReplicaBon plan. The objecBve is to find cerBtude of the Lighthouse ciBes’ demonstraBon validity and feasibility concerning the City of Vaasa’s replicaBon plan. AddiBonally, the aim is to study the soluBons’ potenBal to be implemented in Vaasa, and the benefit concerning the city’s general plans to reach carbon neutrality by 2030. The secondary object is to examine the soluBons’ compaBbility with the IRIS Lighthouse ciBes’ demonstraBons and gathered experiences, and with the recent plans and projects executed in Vaasa related to smart and sustainable mobility soluBons. This thesis was commissioned by the City of Vaasa. European Union launched 2014 the Horizon 2020 program, aiming to encourage EU naBons and their ciBes to take steps to reach carbon neutrality via projects promoBng Smart City development. Horizon 2020’s aim is to baRle climate change by encouraging ciBes to become more sustainable. By promoBng innovaBve, efficient, far-reaching and replicable soluBons, from the fields of smart energy producBon and consumpBon, traffic and mobility, informaBon communicaBon technology, and ciBzen engagement, the objecBve can be achieved. IRIS Smart City project (Integrated and Replicable soluBons for co-creaBon in Sustainable ciBes) was launched in 2017. The project consists of three Lighthouse ciBes and four follower ciBes. Vaasa has been part of the project since 2017 as a follower city. The IRIS project’s soluBons are first to be studied and demonstrated by the Lighthouse ciBes and then to be replicated by the follower ciBes. A replicaBon plan is required to examine and present the feasibility and validity of the integrated soluBons, to secure their implementaBon process. The results of this thesis indicate that the innovaBve smart mobility soluBons, including V2G and 2nd life baRery schemes presented in the City of Vaasa’s replicaBon plan, are relevant to the City of Vaasa, by being compaBble with the city’s climate and decarbonizaBon goals and related sustainable mobility plans and projects executed in Vaasa in the past few years. These soluBons play significant role in the Lighthouse ciBes’ demonstraBons, thus showing great potenBal for uBlizaBon in the City of Vaasa’s infrastructure, mobility and smart grid development plans. The soluBons can advance Mobility as a Service concept, electric vehicle uBlizaBon development, and aid in decarbonizaBon, enhancing energy efficiency, creaBng new businesses and services, and improving the aRracBveness of the city.. Keywords: Horizon 2020, IRIS, Smart City, InnovaBve mobility soluBons, sustainability.

(3) 3. Contents IntroducBon. 9. 1. Horizon 2020. 12. 2. Smart CiBes. 15. 2.1. Smart Grid. 18. 2.2. Smart Transport. 24. 2.3. Electric vehicles and e-mobility. 25. 2.3.1 Hybrid electric vehicles (HEVs). 26. 2.3.2 Plug-in hybrid electric vehicles (PHEVs). 27. 2.3.3 BaRery electric vehicles (BEVs). 27. 2.4. Smart charging. 29. 2.5. Vehicle-to-grid soluBons. 32. 2.6. Second life baReries. 33. 2.7. Mobility as a Service (MaaS). 38. 3. Horizon 2020 Lighthouse projects. 40. 4. IRIS - Integrated and Replicable SoluBons for Co-CreaBon in Sustainable CiBes. 43. 5. TransiBon Track #2 & #3 acBviBes in the IRIS Lighthouse ciBes. 46. 5.1. Gothenburg, Sweden – T.T. #2 and T.T. #3 soluBons and demonstraBons. 48. 5.2. Nice, France – T.T. #2 and T.T. #3 SoluBons and DemonstraBons. 54. 5.3. Utrecht, Netherlands – T.T. #2 and T.T. #3 SoluBons and DemonstraBons. 60. 6. Finland’s NaBonal Climate and Sustainable Mobility Goals. 66. 7. Vaasa’s DecarbonizaBon and Sustainable Mobility Goals. 68. 7.1. The Covenant of Mayors. 70. 7.2. Sustainable mobility plan, MoveIT project, and BothniaTM project. 71. 8. Vaasa’s IRIS replicaBon plan. 77. 9. IRIS - ReplicaBon AcBviBes of TransiBon Track #2 and #3 in Vaasa. 81. 9.1. UBlizing 2nd life baReries for smart large-scale storage schemes. 81. 9.2. TransiBon track #3: Smart e-Mobility sector. 85. 9.2.1. Smart solar V2G EVs charging. 87.

(4) 4. 9.2.2. InnovaBve Mobility services for the CiBzens 9.2.3.. 92. Conclusions on ambiBons and planning concerning acBviBes for the T.T. #3. Smart e-Mobility Sector. 101. 10. The development of the T.T. #2 and #3 replicaBon acBviBes in Vaasa. 103. 11. Conclusions. 109. References. 114.

(5) 5. List of tables. Table 1. The suitable applicaBons for Lithium-ion baReries ..........................................37 Table 2. MaRers of potenBal and challenging aspects of Gothenburg’s demonstraBon of the soluBon, UBlizing 2nd life baReries for smart large-scale storage schemes .............49 Table 3. MaRers of potenBal and challenging aspects of Gothenburg’s demonstraBons of the soluBon, InnovaBve mobility services for the ciBzens .........................................53 Table 4. MaRers of potenBal and challenging aspects of Nice’s demonstraBons of the soluBon, UBlizing 2nd life baReries for smart large-scale storage schemes ....................56 Table 5. MaRers of potenBal and challenges of Nice’s demonstraBons of the soluBons, Smart solar V2G EVs charging, and InnovaBve mobility services for the ciBzens ..........59 Table 6. MaRers of potenBal and challenges of Utrecht’s demonstraBons of the soluBon, UBlizing 2nd life baReries for smart-large scale storage schemes .........................63 Table 7. MaRers of potenBal and challenges of Utrecht’s demonstraBons of Smart solar V2G EVs charging, and InnovaBve mobility services for the ciBzens soluBons ..............65 Table 8. Planned acBviBes of Sustainable Mobility Plan, which have either direct or indirect link to the IRIS replicaBon plan ............................................................................74 Table 9. Vaasa’s replicaBon plan in full ...........................................................................77 Table 10. The maRers of potenBal and challenges of uBlizing 2nd life baReries in Vaasa .. .......................................................................................................................................83 Table 11. The maters of potenBal and challenges of uBlizing V2G schemes in Vaasa ....90 Table 12. The maRers of potenBal and challenges of InnovaBve mobility services for the ciBzens, in Vaasa.............................................................................................................95 Table 13. EU financial instrument for TransiBon Track #3 ............................................101 Table 14. The common objecBves between Sustainable Mobility Plan, Bothnia TM and MoveIT projects, and their connecBon to the City of Vaasa’s IRIS replicaBons plan’s 2nd life baRery, and Smart e-Mobility soluBons .................................................................108.

(6) 6. List of figures Figure 1. Smart city concept ...........................................................................................17 Figure 2. Smart grid components ...................................................................................21 Figure 3. Vehicle-to-grid (V2G) operaBng model............................................................33 Figure 4. IRIS TransiBon Tracks and the integrated soluBons .........................................45 Figure 5. Vaasa’s strategies, policies, plans and programs related to carbon neutrality goals and sustainable transport .....................................................................................72 Figure 6. Passenger cars; PHEVs and BEVs, in Finland ....................................................82 Figure 7. Ravilaakso replicaBon area shown in red ........................................................85 Figure 8. LocaBon of e-charging staBons in Vaasa..........................................................87 Figure 9. EC2B governance model for Ravilaakso district...............................................98 Figure 10. Lighthouse ciBes’ common posiBve and negaBve factors on UBlizing 2nd life baReries for large smart scale storage schemes ..........................................................104 Figure 11. Vaasa’s posiBve and negaBve similariBes on UBlizing 2nd life baReries for smart large-scale storage schemes with the LH ciBes ..................................................105 Figure 12. Lighthouse ciBes’ common posiBve and negaBve factors on V2G and Smart e-Mobility soluBons .....................................................................................................106 Figure 13. Vaasa’s posiBve and negaBve observaBons about Smart e-Mobility with the LH ciBes ........................................................................................................................107.

(7) 7. AbbreviaBons BESS. BaRery energy storage system. BEV. BaRery electric vehicle. BIM. Building informaBon model. BMS. BaRery management system. CIM. City informaBon model. CIP. City informaBon plagorm. DER. Distributed energy resources. DG. Distributed energy generaBon. DMS. Demand side management. DSO. DistribuBon system operator. e-. Electric-. ESS. Energy storage system. EC2B. Easy-to-Be (Mobility as a Service model). EMS. Energy management system. EU. European Union. EV. Electric vehicle. FC. Follower city. GHG. Greenhouse gas. G2V. Grid-to-Vehicle. HEV. Hybrid electric vehicle. IC. Internal combusBon engine. IS. Integrated soluBon. LH. Lighthouse city. MaaS. Mobility as a Service. PHEV. Plug-in electric vehicle. PV. Photovoltaics. QoL. Quality of Life. RES. Renewable energy source. RESS. Remote energy storage system.

(8) 8. SOC. State of charge. SOH. State of health. TSO. Transmission system operator. T.T.. TransiBon Track. V2G. Vehicle-to-Grid. VPP. Virtual power plant.

(9) 9. Introduc6on Climate change, global warming, rising emission levels, and increased energy consumpBon have led naBons across the world to iniBate decisive measures to restrain, control and turn the negaBve development concerning the climate, environment and ulBmately the future of our planet. During the past three decades, several internaBonal climate agreements have been raBfied to stop the global warming, and decrease the carbon dioxide (CO2) levels produced mainly by energy producBon and consumpBon, traffic and agriculture. As governments have set goals for the next decades to reduce emissions, and strive to beRer energy efficiency, they are also facing considerable challenges. Large ciBes are expanding in size and inhabitants, due to the Earth’s growing populaBon and the trend of urbanizaBon. Thus, polluBon levels and emissions from energy producBon and consumpBon are increasing. AddiBonally, the urban traffic and the emissions caused by it are increasing. CiBes are one of the key factors in the fight against climate change. MiBgaBng measures performed in the ciBes concerning energy producBon, consumpBon, traffic, and related emission, have a direct impact on the future of our planet.. European Union (EU) launched 2014, the Horizon 2020 program, aiming to encourage the EU naBons and their ciBes to take acBon to reach carbon neutrality through projects striving to Smart City development. Over the next 7 years, 17 different Smart City project received funding and were launched. Each project was led by 2-3 Lighthouse ciBes (LH) from various EU countries, which were joined by 4-6 follower ciBes (FC). Every Horizon 2020 Smart City program’s project share similar goals, although their soluBons to achieve them may differ. The main objecBve of each project is to baRle climate change by innovaBve, efficient, far-reaching and replicable soluBons, from the fields of smart energy producBon and consumpBon, traffic and mobility, informaBon communicaBon technology (ICT), and ciBzen engagement. Horizon 2020 funded IRIS Smart City project (Integrated and Replicable soluBons for co-creaBon in Sustainable ciBes) was launched in 2017. The Lighthouse ciBes in the five-year project are Utrecht (Netherlands), Gothenburg (Sweden) and Nice Côte d’Azur (France). The follower ciBes.

(10) 10. are Alexandroupolis (Creek), Santa Cruz de Tenerife (Spain), Focsani (Romania) and Vaasa (Finland).. The City of Vaasa’s climate objecBve is to reach carbon neutrality by 2030. In order to achieve this goal, the city has taken several measures during the past decade. It has been involved with the EU’s The Covenant of Mayors climate program since 2016. In addiBon, several projects and reports have been carried out concerning sustainable mobility and urban development, smart grid advancement, and ciBzen engagement. Furthermore, the City of Vaasa’s infrastructure and traffic planning, construcBon and mobility design and acBvity, and energy consumpBon and producBon, are implemented in a sustainable manner, thus promoBng decarbonizaBon.. The City of Vaasa was accepted to the IRIS Smart City project in 2017. IRIS is constructed from five different TransiBon Tracks (T.T.), all including variety of integrated soluBons (IS), measures by which the objecBves set by the Horizon 2020 program can be achieved. IRIS consists of 16 soluBons. First, they are to be researched and demonstrated by the Lighthouse ciBes, and alerwards replicated by the follower ciBes. However, in order to reach actual replicaBon and implementaBon of the soluBons, a thorough replicaBon plan must be developed. In the starBng stage of the IRIS project, the City of Vaasa expressed its interest in replicaBng all 16 of the replicaBon plan’s integrated soluBons. However, some of the soluBons have proven to be more feasible for the City of Vaasa to be replicated than others. AddiBonally, concerning some of these soluBons, considerable measures have already been taken, e.g. in the development of the city’s heat network, energy producBon, smart grid soluBons, and various construcBon projects.. The IRIS projects’ TransiBon Track #2 and #3 consist of soluBons concerning innovaBve mobility services for the ciBzens, vehicle-to-grid (V2G) technology, and uBlizing second life (2nd life) baReries in large-scale storage schemes. These soluBons are also of interest to the City of Vaasa. Smart e-mobility schemes and the development of Mobility as a Service (MaaS) concept present high potenBal for replicaBon and final implementaBon. V2G soluBons and uBlizing 2nd life baReries have also potenBal and significance,.

(11) 11. however, more in the future perspecBve. Yet, the replicaBon plan examines them as well.. Currently, traffic represents approximately 30% of Vaasa’s CO2 emissions. This share is esBmated to increase in the future. The IRIS project’s measures targeted at innovaBve mobility soluBons, and the Lighthouse ciBes’ mobility, V2G and 2nd life baRery soluBons have to comply with the City of Vaasa’s general decarbonizaBon plans, and the designed infrastructure and traffic projects, in order to have significance and validity for the replicaBon plan. In addiBon, the replicaBon plan needs not only to find support and example from the Lighthouse ciBes’ demonstraBons and experiences. AddiBonally, it needs to find cohesion with the other mobility related plans and projects done in Vaasa in recent years. The findings and collecBve voice of these projects, and informaBon about the importance of sustainable e-mobility, faster adopBon of electric vehicles, and development charging infrastructure and mobility services, can aid the City of Vaasa’s decision-making processes and carbon free development..

(12) 12. 1. Horizon 2020 The 2008 financial crisis, and the necessity to cope with its impacts on the European economy, iniBated several incenBve programs and projects in the European Union. The most significant challenges were to find measures to stabilize the financial and economic system in short-term, as well as to protect and create new economic growth and opportuniBes for the future. The EU’s economy, and compeBBveness in global scale, needed thorough structural reformaBon and fiscal consolidaBon. Thus, research and innovaBon became top prioriBes in the new Europe 2020 strategy, receiving significant funding and investments. Based on the strategy, the European Union would strive to generate substanBal amount of new smart technological and scienBfic breakthroughs, hence creaBng new business opportuniBes and jobs via innovaBve products and services. FighBng climate change and adapBng to its impacts, reducing emission levels, reforming energy producBon and efficiency, and advancing sustainable and comprehensive economic growth, became the basis of the Europe 2020 strategy (European Commission, 2011 & 2017).. The EU ushers its member states to turn away from non-renewable, fossil-fuel based energy producBon, to sustainable and renewable energy, e.g. wind, solar, hydro, wave, geothermal energy and waste incinerated heat. The endeavors to achieve carbon neutral socieBes require various asserBve acBons, including developing ciBes to become more environmentally friendly, i.e. smart. Smart ciBes uBlize innovaBvely both centralized and decentralized energy producBon with strong renewable energy sources (RES) involvement, and emphasizing energy efficiency and sustainability. Smart ciBes exploit smart grid and micro grid concepts, electrified transport, i.e. e-mobility, and robust informaBon communicaBon technology, to reduce their carbon footprint. Furthermore, new technologies and innovaBons provide tools for more efficient and encompassing energy services for these ciBes’ ciBzens and businesses. In 2011, the EU’s Head of State and Government, urged the European Commission to combine all of the exisBng EU’s funding for research and innovaBon under one joint strategic framework. The extensive cooperaBon and consultaBon between the European Parliament and mulBple key stakeholders lead to the design of the Horizon 2020 program, which was eventually.

(13) 13. launched in 2014 (European Commission, 2011 & 2016; Garrido-Marijuan et al., 2017; The IRIS Smart CiBes ConsorBum, 2019).. The EU is commiRed to an ambiBous decarbonizaBon of its economy and environment. Diminishing harmful emissions, while constantly adapBng to the growing climate and environmental pressure and urbanizaBon, are vitally important measures in achieving this objecBve. Once iniBated, the Horizon 2020 program became the Europe 2020 strategy’s flagship iniBaBve. The Horizon 2020 is the biggest research and innovaBon program in the history of the EU, being the main instrument and framework to enable the implementaBon of the EU’s research and innovaBon undertaking. The program’s architecture was deliberately designed to be simple, in order to avoid unnecessary bureaucracy, and to facilitate most effecBvely the access and launch of the parBcipaBng projects. The Horizon 2020 incites market driven innovaBons and research projects, thus aiming at direct economic incenBves (European Commission, 2011, 2017 & 2020).. By combining all exisBng EU research and innovaBon funding, the Horizon 2020’s accumulated available funding when launched was €77 billion. This amount was to be addressed to various EU smart city projects to be iniBated over the next seven years, 2014-2020, each to have a duraBon of five years. Thus, although the Horizon 2020 came to its end in 2020, its funded projects carry on their smart city development and the Horizon 2020’s legacy to the next decade and beyond. It is also the highest aspiraBon of Horizon 2020, that each of its funded smart city project and each city involved, conBnue their work to evolve towards ever smarter and more sustainable city environments in the future, and to inspire other ciBes to follow their example of sustainability and low-carbon development (European Commission, 2011, 2017 & 2020).. The Horizon 2020’s foundaBon and main objecBve is to promote sustainable development, which received nearly 60% of the program’s preliminary budget. The rest of the 35% of the budget was designated to consolidated climate and environmental objecBves. Principally, the Horizon 2020’s main-focus areas receiving funding were:.

(14) 14. • To build a low-carbon and climate resilient future. • Encourage circular economy and connecBvity in environmental and economic fields. • Promote robust digitalizaBon of European industry and services. • Develop the adopBon of electric vehicles and their penetraBon to automoBve markets, next generaBon baRery technologies, and schemes to advance the progress of carbon-free society.. The Horizon 2020 had several mutually reinforcing themaBc secBons to support its endeavors, including excellent science, industrial leadership, societal challenges, innovaBon in small and medium sized enterprises, access to venture capital, and spreading parBcipaBon with excellence and knowhow. Thus the Horizon 2020, through funding for potenBal smart and sustainable projects, it aimed to ensure the EU’s long-term compeBBveness via state-of-the-art research and innovaBon acBvity. Moreover, the program strived to make the EU more profitable for investments and businesses related to smart technologies and innovaBons (European Commission, 2011, 2017 & 2020) . By securing sufficient financing, the Horizon 2020 was able to maximize the growth potenBal of the European smart energy technology, research and innovaBon work, and sustainable development of businesses. In addiBon, the Horizon 2020 approached societal challenges by distribuBng funds to following focus points:. • All-embracing, innovaBve, digital, secure and well-being socieBes • Climate acBon, resource efficiency and raw materials • Smart, secure, clean and efficient energy • Smart, green, electrified and integrated transport (European Commission, 2011 & 2020).

(15) 15. 2. Smart Ci6es Currently, more than 50% of the world’s populaBon is concentrated in ciBes, or in their close proximity. It has been esBmated, that by 2050 that share has risen by addiBonal 20%. In 2016, there were 28 megaciBes in the world, with populaBon more than 453 million combined. According to many esBmaBons, the number of these megaciBes will be over 40 by 2030. UrbanizaBon is a global megatrend, which has direct effects on climate change, rising emission and polluBon levels, and the requirements of energy producBon, distribuBon and consumpBon. AddiBonally, urbanizaBon’s impacts on infrastructure requirements and land use, residenBal and transport requirements, and sustainability on all of its levels: environmental, economic, social and cultural (Sloman, 2017; Cassandras, 2016).. The accelerated urbanizaBon and growing environmental awareness have risen concerns and demands to develop ciBes smarter, with the ability to be constantly evolving. There is a need for ambiBous sustainability strategies, which aid ciBes intelligently and comprehensively by integrated technological soluBons, and which can be demonstrated on a larger scale, to reach their smart city objecBves. Smart city development promotes innovaBve energy soluBons, smart grid and RES development, and strives to advance sustainable transport modes, thus affecBng on economic and social levels, and enhancing quality of life (QoL). A smart city uBlizes ICT to reach more efficient and intelligent standards in achieving carbon neutrality. It preserves natural resources, and reduces land use by mature and jointly executed coordinaBon, planning of infrastructure and transport design. A smart city strives for implementaBon of green and innovaBve technical soluBons, leading to savings in cost and energy, and promoBng beRer service delivery (Cassandras C.G., 2016; IEC, 2014; Ferrer et al., 2017; The IRIS Smart CiBes ConsorBum, 2019).. A city can evolve smarter by transforming the exisBng urban infrastructure gradually to meet the requirements of a smart city. In addiBon, a city can design and construct new city districts, infrastructure and environment by uBlizing the smart city procedures and soluBons. These districts will act as example areas, i.e. living labs, and consequently.

(16) 16. cause changes in adjacent city districts towards smart city development. The smart city advancement should have a holisBc approach on sustainability. Measures to reduce a city’s impact on environment and to expedite the integraBon of intelligent and efficient use of technologies with the urban infrastructure outright form the backbone of environmental sustainability. Economic sustainability signifies aRempts to develop a city’s economic potenBal, new financial and business models and innovaBons, and advance more efficient and annexed service and infrastructural soluBons. A smart city’s aRracBveness for people, businesses and capital, improves the overall employment, business and service possibiliBes, when social sustainability is funcBoning properly. Thus, cost reducBons, higher stability and security, and enhancement of quality of life can be achieved (IEC, 2014; Ferrer et al., 2017).. In order to plan, capitalize and implement the best operaBng smart city soluBons, new methods, technologies and innovaBons are required. These include efficient and affordable energy producBon based on RES, and invesBng in the development of e-mobility soluBons, smart charging and energy storage schemes, and advanced ICT soluBons. AddiBonally, key stakeholder engagement is relevant, including poliBcal leaders, government and city officials, organizaBons, service operators and soluBon providers, investors and consumers. Furthermore, local level ciBzen engagement has a paramount role in smart city development. By these means, the conBnuance of the smart city development can be secured, including the opBmal end-result of ciBzen-awareness and aRracBve city environment (IEC, 2014; Ferrer et al., 2017)..

(17) 17. Figure 1. Smart city concept (Singh, 2014). Smart city development can face challenges. They can be financial, technical, social or administraBve. CollaboraBon between different stakeholders may prove to be problemaBc. LasBng and successful partnerships might be difficult to establish. Disagreements about planning, means, prioriBes and objecBves might emerge. Capital may be insufficient, or the procurement rules are not appropriate or clear to everyone involved. There may be issues with insufficient standards, regulaBons, even laws. The required infrastructure may not be mature enough to hold the integraBon of a planned smart soluBon. Lack of required competence or deficiency of necessary local administraBve capacity may hinder the development. Resistance to change might occur from any of the key stakeholder groups. Moreover, the successful development of a smart city soluBons and technology, which are easily adoptable by the society, user-friendly and reliable, is not self-evident (Ferrer et al., 2017; Van Steen, 2019, IEC, 2014).. Designing the different sectors of a smart city, indicated in the Figure 1, and predicBng the requirements, consequences and benefits of the smart transformaBon, can be challenging. In order to evade unnecessary hindering factors and challenges, well-de-.

(18) 18. signed and thoroughly carried out interoperability is vital, alongside with resorBng to internaBonally agreed standards and technical specificaBons. Successful coalescence of smart infrastructure, technology and exisBng environment is imperaBve for value creaBon and in order to reach the objecBves of a smart city’s predesigned framework. By joining horizontal and verBcal integraBon methods, beRer value, robust quality standards and interoperability can be obtained. Thus, the stakeholder involvement can be strengthen, necessary supply chains enhanced and boRlenecks avoided. This is also beneficial in order to keep the related costs under control, advance the efficiency of the measures required, and ulBmately support and improve the smart energy technologies’ business environment. By uBlizing both boRom-up and top down strategies for knowledge, informaBon and intelligence processing, a smart city’s measures for sustainability, service development, data centricity and successful ciBzen engagement can be achieved more efficiently. Thereby, the smart city development benefits from immediate feedback from its environment and key stakeholders, all joining and being in contact with the smart city progress and inducements (IEC, 2014; Ferrer et al., 2017; Van Steen, 2019).. 2.1. Smart Grid The infrastructures of power systems, from electricity generaBon to uBlizaBon industrially, commercially and residenBally, are currently in the state of significant change. The power systems, i.e. grids, are required to evolve, to become smarter. Today’s power grid needs to be reliable and efficient, resilient and flexible, secure and technically advanced, controllable and customer friendly. The main drivers for these requirements are the rising global populaBon, urbanizaBon, and environmental issues, e.g. the climate change, global warming and increased emission levels. They all have an influence on internaBonal and naBonal energy and environmental policies, laws and regulaBons around the world. AddiBonally, advances in technology, and increased uBlizaBon of renewable energy sources steer the development of the power systems towards a new age (Malik, 2013; Rodriquez-Molina et al., 2014; Varaiya et al., 2011)..

(19) 19. The start of power systems dates back nearly 140 years. The first power staBon in the world, Edison Pearl Street GeneraBon StaBon, located in lower ManhaRan, New York, USA, and started its operaBon in 1882. Since then, power systems have developed into large central power generaBng staBons, supplying electricity through high-voltage networks to local distribuBon systems, serving all levels of consumpBon: industrial, commercial and residenBal.. A tradiBonal power grid uses large power plants to produce raw electricity. The power plants are directly connected to the high voltage (HV) networks through centralized synchronous generators with high inerBa. The HV networks distribute power to medium voltage (MV) networks and industrial customers through HV/MV substaBons. MV/ LV distribuBon substaBons conduct power to low voltage networks with commercial and domesBc customers. Transmission system operators (TSO) provide the power grid infrastructure, covering long distances. TSOs are also in charge of the offer and demand balance of the grids. DistribuBon system operators (DSO) are responsible for the features related to end-user connecBvity concerning the power network (Rodriquez-Molina et al., 2014; Malik, 2013; Varaiya et al., 2011; Ye, 2018).. A modern power system’s ideal requirements are high reliability, quality, flexibility and efficiency in energy supply. AcBve monitoring and fast reacBon to any changes in the power delivery system are also uncondiBonal qualificaBons. Reliability is needed in balanced electricity supply, improved energy efficiency, and constant voltage and frequency control. Moreover, increased integraBon of renewable power generaBon, electricity storage systems, e.g. baRery-energy storage soluBons (BESS), and the rising number of EVs, set their own demands for power grids. Furthermore, digitalizaBon and increased impact of new technology, wireless communicaBon, and new generaBon security threats, raise the level of requirements for the funcBonality of current power systems even higher. Modern power grid is required to be self-healing in case of power disturbances, and resilient to stand all aRacks, physical and cyber. Efficiency in providing local and system-wide technical services and endeavour to minimize network losses are essenBals as well..

(20) 20. Unfortunately, the tradiBonal electric power system infrastructure is not designed to meet these vast requirements. It is designed on the operaBng model, where electricity flows primary in one direcBon, from HV generaBon sources to MV and LV level consumpBon. It has limited cross-border interconnecBons, relying on centralized control. The tradiBonal power systems are dependent on non-renewable energy sources (coal, gas, petroleum), which cause approximately 40% of the global carbon dioxide (CO2) emissions, thus having severe negaBve impacts on the environment. Furthermore, tradiBonal power systems are technically opBmized for regional power adequacy, and are able only for limited automaBon and situaBon awareness. They lack customer-size data to manage and reduce energy use sufficiently for today’s standards (Malik, 2013; Rodriquez-Molina et al., 2014; Isaacs, 2004; European Commission, 2006; Varaiya et al., 2011).. European Commission’s defines a Smart grid as an electricity network that can cost efficiently integrate the behaviour and ac8ons of all the users connected to it - generators, consumers and those that do both - in order to ensure an economically efficient, sustainable power system with low losses and high levels of quality and security of supply and safety (European Commission 2011).. Smart grids - provide enhancements and expansion to the tradiBonal power grids, their maintenance and operaBons, by being flexible, opBmal and bidirecBonal. As illustrated in the Figure 2, Smart power generaBon is coordinated, and locally managed, having full integraBon of distributed energy generaBon (DG) with RES (wind, solar (PV), hydro, wave, geothermal, bio and waste-energy), alongside with large-scale centralized power generaBon. Smart grids provide enhanced sensory and control capacity, designed to deliver and perform at high-speed, in near- or real-Bme, in order to adjust to integrated DG, RES, energy storage units, EVs, direct consumer parBcipaBon in energy management (consumpBon and producBon), and efficient communicaBon appliances. Smart systems aim to provide user specified secure, quality and reliable power supply for the digital age. The customers are provided with beRer tools to manage their energy consumpBon, not only to act as consumers but having the ability to perform as energy producers as well. With improved economic producBvity, high-class demand.

(21) 21. side management (DMS) and customer-driven value-added services, consumers can benefit from cost savings and increment in quality of life.. Figure 2. Smart grid components (Lohrmann, 2017).. Minimized environmental impact can be achieved by maximizing safety and sustainability. Smart grid’s operaBon and technology are designed to meet the demands of modern cyber security, and to assure long-term operaBon of the whole power system. Latest advances in wireless communicaBon technology and intelligent informaBon management systems are uBlized, in order to secure the most robust and dependable operaBon, control and monitoring (Malik, 2013; Rodriquez-Molina et.al, 2014; Isaacs, 2004; European Commission, 2006 & 2011).. Smart grid operaBng model includes also the concept and acBvity of microgrids and virtual power plants (VPP). Both have become more common by the development and decentralizaBon of the power systems. A microgrid is a local cluster of electricity loads.

(22) 22. and sources, operaBng connected and synchronously with the actual wide area power system. A microgrid can be disconnect to "island mode” if necessary, thus funcBoning autonomously apart from the actual grid. Microgrids’ features include heavy integraBon of DG sources and RES. Prevalence of microgrids has dramaBcally increased during the past 12 years when various communiBes, commercial buildings, public insBtuBons, universiBes and military installaBons have started to uBlize the opportuniBes of decentralizaBon of power systems.. A virtual power plant is a coaliBon or system of suppliers, which generates power for independent consumpBon, and takes acBvely part in energy sales by uBlizing RES, energy storage systems (ESS) and cloud-based technology. VPP acts as one large, virtual and controllable power plant, ensuring its suppliers an opportunity to operate as a unified and flexible resource in the energy market, simultaneously achieving energy selfsufficiency.. Microgrids and VPPs have in common their compilaBons and opBmizaBon of distributed energy resources. The biggest difference is that microgrids have a confined network boundary and ability to operate in island mode. Whereas, VPPs can stretch over much wider geography, being able to alter size depending upon real-Bme market condiBons. The increasing number of microgrids and virtual power plants bring more flexibility to the power systems. The most relevant drivers for this development have been the evoluBon of the smart grid concept and its supporBng technological innovaBons, including DER, reducBon in costs of consumer sized solar energy and energy storage technology. In addiBon, efforts to cut down energy costs in general, and global policy efforts to reduce greenhouse gas emissions have contributed to the increment of microgrids (Hanna et al., 2017; Rodriquez-Molina et al., 2014; Ye, 2018; Bavrani et al., 2017).. The smart power systems allow the electricity markets to develop into plagorms operated by large number of different market actors. The trend is moving away from the tradiBonal wholesale market structure towards retail markets, including acBve consumers with energy producBon capabiliBes to act as producers. The level of compeB-.

(23) 23. Bon increases, thus enabling beRer incenBves for cost efficiency and enhance innovaBons. The consequences are extensive and require capability for greater flexibility in the interacBon between demand and supply. A smart grid does not focus solely on the wholesale market, instead it includes all market segments, including trading. A smart power system takes into account the end-user behaviour, hence affecBng the energy market as a whole. The posiBve outcomes include requirements for market operaBons’ increased efficiency, reducBon in energy costs, and the development of the future’s decarbonized grid. AddiBonally, consumers gain the possibility by smart meters and twoway communicaBon, to enhance their energy consumpBon management, cut costs and act as energy producers for the grid, with measures such as PV energy, separate energy storages and/or with EVs through their baReries (Greve, 2016; Green & Webb, 2016; Ye, 2018).. In smart grids both producers and consumers are making decisions concerning consumpBon, based on prices signalling Bmely the true marginal cost of changing energy demand, instead of having tradiBonal flat-rate tariffs with no or liRle possibility to contribute to the energy costs. This dynamic and real-Bme pricing allows the energy markets to fully exploit and reward its generaBng capability, thus giving way for flexible and smart “energy-only” market, promoBng new business models.. One possible model, which delivers more control and cost effecBveness to network providers and transparency of prices for consumers, connects these two operators in an evolved market infrastructure, focusing on the potenBal of trade of energy service rather than just simply trading energy. The network operators are able to trade more efficiently on mulBple plagorms, and with mulBple operators: industrial, commercial, domesBc, microgrids, VPPs, EVs etc. AddiBonally, technology companies can sell power alongside the meters and/or other devices controlling the consumpBon (Greve, 2016; Green, 2016; Ye, 2018)..

(24) 24. 2.2. Smart Transport Some of the biggest transport related challenges in today’s growing ciBes are congesBon, polluBon, accidents, noise and scarceness of public space. Enhancing the development of diverse transport systems and technology, require deployment of Mobility as a Service concept (MaaS), urban mobility governance, and real-Bme data collecBon and management. Thus, beRer traffic and infrastructural planning and management can be achieved. AddiBonally, there are maRers of social nature to be considered, such as beRer ability to improve traffic safety, enhance environmental performance and attracBveness, and advance informaBon management and decision-making. UlBmately, the goal is more sustainable and well-funcBoning urban surroundings, with the ability to provide beRer quality of life to the ciBzens by efficient, secure and sustainable mobility, energy technology and ICT soluBons (Van Oers et al., 2020; Surdonja et al., 2020).. Through state-of-the-art energy technology, sustainable transport and ICT soluBons, a smart city benefits from improved and precise quality and quanBty measurements, aided by real-Bme big data management, analyBcs and modelling. Consequently, gained development in knowledge capacity building, transfer and lessons learned, enable and amplify the city’s smart aspiraBons. Smart transport, both individual mobility and public transport, seek to support and exploit ways of e-mobility systems, conBnuous mobility chains and new mobility services, which are not only efficient and userfriendly, but cost-effecBve as well (Van Oers et al., 2020; Porru et al., 2020; Dudyck & Piatkowski, 2018).. Private and public transport’s transiBon from internal combusBon engine (IC) vehicles to electric, gas and bio fuel vehicles helps to decrease fossil fuel consumpBon, hence helping to achieve carbon neutrality in smart ciBes. Transmission from private car ownership towards car sharing, i.e. car-pooling, and enhanced smart public transport services and increased connecBvity, result in more sustainable transport in general, with decreased volume and emission levels, opBmized to meet the demands and requirements of inter-modality. Smart public transport systems is highly flexible, providing consumers more versaBlity in transport modes, routes, schedules, service providers.

(25) 25. and payment systems (Van Oens. et al., 2020; Porru et al., 2020; Dudyck & Piatkowski, 2018).. UBlizaBon of advanced EV technology and related soluBons, e.g. smart charging and V2G schemes, with opBon of combining RES and/or remote energy storage systems, are all part of a smart mobility’s structure and integraBve soluBons. FuncBoning MaaS concept provides aRracBve and sustainable alternaBve for private transport and vehicle ownership. It avails of intelligent mobility systems, e.g. data management, ICT and real-Bme informaBon access. Costs concerning traffic and travel can decreased, congesBons be miBgated, and Bme used in travelling reduced. AddiBonally, the safety factors of traffic can be enhanced, and polluBon and noise levels reduced. Furthermore, smart mobility contributes to the overall design of smart ciBes by transport network’s efficiency, beRer management of parking spaces, and advancing public transport’s usage rate and its supporBng policies (Van Oers et al., 2020; Surdonja et al., 2020; Dudyck & Piatkowski, 2018; Barone et al., 2014).. 2.3. Electric vehicles and e-mobility Electric vehicle (EV) was invented already in the early 1830’s, decades before the first IC engine vehicle invenBon, taking place later that same century. Electric vehicles were common unBl the 1930’s, when their share out of the automoBves started to diminish, due to their insufficient driving power, overall slowness, short driving range and high price. The IC vehicles had reached much higher popularity during the 1920’s, because of beRer performance factors, affordability, and invenBon of mass-producBon. It was not before the early 1990’s, aler sufficient advancements in power electronics and microelectronics technologies, when the hybrid EV producBon could start in the United States (Sharma et al., 2020; Pavic et al., 2020; Mullan et al., 2012; Matulka, 2014).. During the first two decades of the 21st century, the demand for EVs has increased steadily. The main reasons for this development have been general increment in environmental awareness, EVs’ much lower carbon emission and air polluBon levels, considerably lower oil use, reducBons in model prices, and improvements concerning.

(26) 26. power performance, driving range, charging and safety. AddiBonally, external factors such as fuel prices, availability of charging staBons and development in consumer characterisBcs have improved the advancement of EVs adopBon and penetraBon into automoBve markets around the world. Moreover, the poliBcal, economic and environmental accord over the risks of transport systems’ dependency on petroleum-based fuels has contributed to firming the foundaBon for EVs’ ascent (Sharma et al., 2020; Pavic et al., 2020; Mullan et al. 2012; Matulka, 2014).. There are three types of electric vehicles.. 2.3.1 Hybrid electric vehicles (HEVs) HEVs represent the most proven and market established EV type. A HEV is powered by an IC engine, which receives addiBonal power from an electric motor. The uBlized electricity is produced either by the IC motor running an electric generator, or from kineBc energy, which is harnessed via regeneraBve breaking, and consequently transformed into electricity. HEVs are further divided into three subtypes.. •. Series HEV: a combusBon engine drives an electric generator, which charges a baRery, providing power to the electric motor. Only the electric motor supplies power to the wheels. No mechanical connecBon between the IC engine and the transmission exists, thus making it possible for the IC engine to operate at maximum efficiency.. •. Parallel HEV: an IC engine and an electric motor are connected parallel for mechanic connecBon. The IC engine is the primary power source and the electric motor operates as a backup power source or for extra torque.. •. Series-parallel aka combined hybrid HEV: has features from series and parallel HEV types. Series-parallel is the most complex and expensive system of the three HEV types (Pavic et al., 2020; Quinn et al., 2010; Habib et al., 2015)..

(27) 27. 2.3.2 Plug-in hybrid electric vehicles (PHEVs) PHEVs have the capability to run on gasoline or electricity. The ability to use baReries to power an electric motor, which can operate as an alternaBve power source and independently from IC engine for the vehicle, result in petroleum usage reducBon and decreases in CO2 emissions. A PHEV has to be plugged into the power grid for charging. Thus, it possesses the ability to operate in V2G mode, aler required modificaBons have been done for the vehicle.. 2.3.3 BaYery electric vehicles (BEVs) The most advanced electric vehicle type is the baRery electric vehicle (BEV), i.e. pure electric vehicle. BEVs use solely baReries and electric motor to run and have no IC motor. BEVs have to be charged as PHEVs. Some of the newest BEV models have the ability to operate in V2G mode, and the others can be modified for the ability. BEVs have more limited driving range than PHEVs (Pavic et al., 2020; Quinn et al., 2010).. PHEVs’ and BEVs’ technologies are designed to enable unidirecBonal charging from the grid, i.e. grid-to-vehicle (G2V). However, both of these EV types can be designed to enable bidirecBonal charging, i.e. vehicle-to-grid (V2G) mode, thus been able to supply power from the baReries to the grid. Thus, EVs with V2G capability can be uBlized to support the power grid as distributed power storage and supply, and in various ancillary services, e.g. voltage and frequency control, and load following (Drude et al., 2014; Sharma et al., 2020).. BaReries are the most significant and expensive components of PHEVs and BEVs, concerning their compeBBveness. Issues such as cost and climate condiBons are of concern with baReries, as well as energy density and power density, since they affect the allowed driving range. BEVs’ driving range can vary from 100 km to 500 km, depending on the baRery capacity. AddiBonally, the uBlized baRery technology affects a baRery’s cycle life. Lithium-ion based baReries are best suitable for EVs purposes (Lithium-ion aka Li-ion or LIB), parBcularly Lithium Nickel Manganese Cobalt Oxide (LiNiMnCoO2).

(28) 28. and Lithium Titanate aka LTO (Li2TiO3) baReries. Other lithium based baRery technologies include Lithium-iron phosphate aka LFP (LiFePO4), Lithium-Sulfur (Li-S) and Lithium-air (Li-O2) baReries. Although these lithium baRery models are also suitable for EV use, they are more advanced and expensive than common Li-ion baReries, and sBll in the research stage (Sharma et al., 2020; Pavic et al., 2020; BaRery University, 2021).. Since there are various different sizes and model types of EVs, various different baRery models exist as well. The most notable feature of a baRery is the power it can provide. Demanding operaBng temperatures, i.e. extreme hot or cold, have the effect to degrade a baRery, thus acceleraBng the loss of its capacity and reducing its cycle life. Heat has an impact on the baRery by reducing its life, and cold decreases its performance temporarily. The most important EV baRery qualiBes are trip-length capability, amount of peak power delivered during acceleraBon, and energy harnessed during breaking. EV’s baRery management system (BMS) has mulBple tasks to manage. BMS esBmates the baRery’s state of charge (SOC) and state of health (SOH) condiBons, and monitors and balances the baRery’s cell acBvity. In addiBon, the BMS manages the battery’s thermal condiBon, safety and protecBon. Moreover, the BMS is the interacBng component to the charging staBon, implemenBng an opBmal charging profile for the baRery (BaRery University, 2021; BaronB et al., 2016; Sharma et al., 2020).. A small electric vehicle is usually equipped with a 12–18kWh baRery. A mid-sized family sedan baRery has 22–32kWh of power. The most powerful EV models are equipped with large-size baRery, capable of producing 60–100kWh, providing extended driving range and higher performance. Most EV baReries are guaranteed to have a life span of 8-10 years or approximately 160 000 km.. Development in baReries’ cost, lifespan, reliability, sustainability, safety, usability and capacity, are all factors determining EVs’ overall success and advancement in automoBve markets globally. AddiBonally, improvements and design of new baRery material and chemistry soluBons play a crucial role. For example, designs of baRery packs, advancements in lithium-ion and nickel metal hydride (NiMH) technologies and manufacturing processes, and baReries’ recyclability and end-of-life soluBons (e.g. second-life.

(29) 29. baRery schemes), will have significant impact on EVs’ future evolvement and success trajectory (Pavic et al., 2020; BaronB et al., 2016; BaRery University, 2021).. 2.4. Smart charging The fast rising number of EVs require wider, reliable and more comprehensive charging infrastructure. As the number of EVs increases, their potenBal impacts on power grids ascends as well. Hence, efficient smart charging schemes and management become essenBal. In smart charging, an EV and a charging device are in data connecBon. This connecBon is further connected with a charging operator via the charging device. The charging operator/the owner of the charging device is able to monitor, control and restrict the charging remotely, thus opBmizing the energy consumpBon effect to the grid. If charging is not managed controllably, a large number of EVs can cause severe peak loads to the power grid by increased power and energy demand, hence having significant impact on the power quality. Other potenBal effects to the power grid are possible negaBve impacts on the various system components, e.g. transformers. Without regulaBon and control, charging simultaneously a large number of EVs, i.e. fleets, can cause disrupBon to the stability of the whole power system. The rising demand of electricity requires enhanced control of DMS, having the capability and tools to uBlize the capacity harnessed from EVs, their ability of acBng as distributed energy storages and power generaBon units for the grid (BaronB et al., 2016; Mullan et al., 2012; Habib et al., 2015; Sharma et al., 2020).. Different EV charging technologies are:. •. UnidirecBonal vs. bidirecBonal:. The charging of EVs can either be unidirecBonal or bidirecBonal. In the first model, aka grid-to-vehicle (G2V) soluBon, an EV uses the power grid to charge its baRery. In the later model, the EV baRery can also be used to supply power to the grid, i.e. V2G soluBon..

(30) 30. •. On-board vs. off-board chargers:. When an EV is equipped with an on-board charger, it can be charged anywhere, where a power outlet (plug-in) exists. On-board charger adds more weight to an EV. Whereas, an off-board charger requires a charging point or a staBon with power raBng of approximately 50kW to charge the baRery of an EV.. •. Integrated chargers:. An EV’s electric drive system components take part in charging, which reduces the size of an on-board charger, or it is not required at all. Thus, reducBons in cost, weight and space usage can be achieved.. •. Wireless aka dynamic charging:. Electric power is transferred wirelessly to an EV through a power field. The system requires a large size antenna array, which can be supported by inducBve or magneBc resonance coupling, microwaves, or laser radiaBon. However, wireless charging is sBll in the research stage, and its expenditures are high. Yet, once operaBonal and widely available, it has the potenBal to revoluBonize the whole transportaBon system (BaronB et al., 2016; Sharma et al., 2020).. In charging, the current and voltage needs to be constantly controlled. This can be best achieved by either keeping the current or voltage constant. AddiBonally, different levels of charging exist. Level 1 charging or slow charging is designed for residenBal outlets, for on-board charger models with 120V AC ouRake. Level 2 aka semi-fast charging is suitable for charging staBons, and are capable for five Bmes faster charging than the level 1, thus being able to fully charge an EV in 5-7 hours. Level 3 aka fast charging uses DC power with constant current and voltage. Its charging power exceeds 100kW, requiring charging technology of considerable size, thus being suitable only for off-board charging. Fast charging is opBmal, e.g. in public transport and commercial logisBcs usage, where baRery charging should not last more than 30-60 minutes (Sharma et al., 2020)..

(31) 31. However, smart charging soluBons require new kind of charging schemes:. •. Uncontrolled, Bme-of-use smart charging:. Smart charging based on opBmizaBon of Bme-of-use is the simplest form of smart charging. It incites the end-users to uBlize off-peak periods for charging from peak Bmes. AddiBonally, it is relaBvely straighgorward to implement Bme-of-use charging, since its external stakeholder control does not exist. Time-of-use charging has proven its effecBveness in delaying EV charging unBl off-peak periods at low EV penetraBon levels (Paulraj, 2019; Virta, 2021).. •. UnidirecBonal controlled charging (V1G):. Either EVs or the charging infrastructure can adjust their charging rate in unidirecBonal controlled charging. The grid operator oversees the charging process via controlling signals. Daily esBmaBon of the local available charging capacity is provided by Open Smart Charging Protocol (OSCP), and Open Charging Point Protocol (OCPP) to the Charge Point/Spot Operator (CPO), which adjusts EVs’ charging profiles to the available charging capacity.. •. BidirecBonal V2H / V2B / V2X smart charging:. Smart charging scheme, which provides an EV baRery’s power supply to be connected to its close surroundings, performing as a back-up power source increasing self-consumpBon. Hence, it does not stress the actual power grid but funcBons as an alternative power source. This scheme can add flexibility and reliability to, e.g. homes (V2H), buildings (V2B) or some other objects’, e.g. facility, appliances, lighBng etc., electricity consumpBon (Paulraj, 2019; Virta, 2021).. • BidirecBonal Vehicle-to-grid (V2G): With V2G soluBon, an EVs can be uBlized as a distributed power source and storage for the grid. Thus, it is more evolved smart charging method than controlled V1G or bidirecBonal charging for self-consumpBon. Furthermore, in V2G smart charging/discharging, EVs’ baReries can be uBlized in ancillary services, including voltage support and.

(32) 32. frequency control, load following and funcBoning as secondary reserve for grid flexibility and reliability. In V2G smart charging, the TSO is capable of purchasing energy from EV owners if the peak demand requires it. Hence, V2G has higher commercial value, which can encourage consumers to acquire an EV (Paulraj, 2019; Virta, 2021; Habib et al., 2015).. 2.5. Vehicle-to-grid solu6ons Through V2G, EVs can be uBlized as an addiBonal power source to the grid. With great number of EVs, i.e. fleets, V2G operaBng model reduces the dependency on oil, and lowers CO2 emissions. AddiBonally, V2G has the capability to enhance stability, reliability, efficiency, and generaBon dispatch of a distributed network, thus increasing the enBre power grids’ performance. Majority of the EVs are not uBlized in traffic all the Bme. Instead, they spend vast amounts of Bme parked, where they could be connected to the grid. Once staBonary, the baReries of EVs are not uBlized for driving, thus forming an enormous source of distributed energy storage, which could be used as an extension and support to the electricity supply system, in smaller or larger scale. The baReries represent zero-cost energy storage for the grid use, since they already have been purchased for the EVs’ use (Mullan et al., 2012; Habib et al., 2015; Quinn et al., 2010).. V2G concept has major benefits. Large amount of EV baReries have the capacity to store excess electricity during low-demand hours, and release it back to the grid when the energy demand is at its highest, as illustrated in the Figure 3. EV baReries have rapid response Bme for storing energy, and they are capable of providing low-cost aid through various ancillary services, e.g. voltage support, frequency regulaBon, load following and aiding in black starts. In addiBon, EV baReries are able to increase and enhance renewable energy generaBon to the grid, e.g. by interconnecBon with smart homes’ photovoltaic (PV) panels in urban areas, thus balancing and adding stability to the power system. By and large, V2G soluBon can also generate revenue for the all parBes involved: the electricity system operator (SO), aggregators, electricity retailers and the EV owners (Mullan et al., 2012; Habib et al., 2015; Quinn et al., 2010)..

(33) 33. Figure 3. Vehicle-to-grid (V2G) operaBng model (EVConsult, 2021).. 2.6. Second life baYeries EV baReries’ end-of-life purpose raises many quesBons and concerns. Should the batteries be disposed or recycled, or could their purpose be prolonged? Is a baRery sBll usable and does it have any value, aler its capacity and performance levels have declined, i.e. the baRery has reached the end of its “first life”, its original purpose? Nowadays, when circular economy’s procedures and values are common concepts, the maRer of EV baReries’ end-of-life has become more important as well. Finding a “second life” (2nd life) for the used EV baReries is receiving wide aRenBon globally. EV batteries’ second life could benefit the baReries’ manufacturers, user and potenBally create new businesses and revenue streams. Thus, granBng a baRery a second life would have posiBve environmental and economic effects. As transportaBon steadily transforms from IC powered vehicles to electric vehicles, the number of lithium-ion baReries in and out of use rises considerably (IEA 2019; Engel et al., 2019).. Normally, an EV lithium-ion baRery’s first life lasts approximately 8-10 years, aler which it is no longer suitable to funcBon as a baRery in regular EV usage. However, the.

(34) 34. baRery sBll has 70-80% of its capacity lel. Then, three end-of-life opBons exist: disposal, recycling or conBnuance of uBlizaBon in a less demanding baRery applicaBon, e.g. having a 2nd life. Disposal of an EV baRery possesses environmental concerns to be taken into account, the reason why it is a best opBon only for damaged baReries. Moreover, disposal without recycling is not economically sensible. Recycling, i.e. collecBng the baRery’s valuable metals is an expensive procedure. With lithium-ion batteries, it is more expensive to recycle a baRery than it is to mine new lithium. The cost of recycling a baRery is approximately €/kg (10€/kWh), which is three Bmes higher than can be expected from selling the used baRery on the market. Because reclaiming lithium is so costly, less than 10% of all used EV baReries’ lithium are recycled, and vast numbers are been disposed, resulBng great losses in the baReries’ sBll exisBng value. By reusing the baRery and harnessing its 2nd life potenBal, its lifespan’s total use and value can be captured (Jiao, 2016 & 2020; Desarnaud, 2019).. In 2019, the global amount of sold electric vehicles (PHEV & BEV) was over 2 million units, raising the total global number of EVs in use to 7.2 million. According to esBmaBons, in the year 2025 the total number of EVs in the world will reach 100 million, with 25% market share of all cars sold globally in each year. In 2030, over 250 million EVs are expected to exist in use, and approximately 45 million new ones to be sold every year. The ascending development of EV industry will increase the number of out-of-use lithium-ion baReries drasBcally (IEA 2020; Hossain, at al., 2019, Desarnaud, 2019; Engel et al., 2019; Jiao, 2020; Van Troeye, 2019).. According to esBmaBons, in 2030 the accumulated amount of energy generated by the EVs’ lithium-ion baReries in global scale, counBng both new baReries and those taken out of use, will be 3.6-17.6GWh. Some esBmate this amount to be even as high as 200GMh. In 2063, the amount will be anything between 32.3-1010GWh, according to the lowest and most opBmisBc evaluaBons. This development has a descending reflecBon on new lithium-ion baRery prices, which are dropping already regardless this factor, due to their own market development. Currently the price of a new lithium-ion baRery is around $200-300/kWh, whereas in 2025 the price is esBmated to be.

(35) 35. $90-100/kWh. The decrease in prices is due to the increase of number of EVs sold in the markets.. A great potenBal exist for 2nd life baReries in staBonary energy-storage applicaBons, which require less frequent baRery cycling (100-300 cycles/year). If a new EV baRery has 22kWh energy, aler its first life it sBll holds 15-17kWh, which can enable a second life of 10 more years, if uBlized shrewdly (IEA 2020; Hossain, at al., 2019, Desarnaud, 2019; Engel et al., 2019; Jiao, 2020; Van Troeye, 2019).. By fully uBlizing the growing number of 2nd life baReries, the need for new baReries would be lesser, resulBng in reducBon of natural resources’ exploitaBon. Second life baReries present no added burden on the environment. Instead, they enable an affordable energy storage soluBon, able to operate in various staBonary energy-storage applicaBons, and enhance smart grid and renewable energy development. UBlizing 2nd life baReries is scalable, affordable and sustainable. However, for safety reasons, 2nd life baReries require tesBng before they can be uBlized. However, therealer they are a vital mean tackling the growing energy consumpBon issues (Colthorpe, 2019; Jiao, 2016 & 2020). Second life baReries can perform as staBonary primary energy storages in smaller scale, or as back-up storages in more demanding usage. In peak demand, 2nd life batteries can aid in ancillary services such as voltage support, frequency regulaBon, black start and load following, as indicated in the Table 1. They can also be exploited to operate with PV as storage use in microgrid purposes for various premises, municipaliBes and neighborhoods, or even in small town scale, funcBoning for the local smart grid. In transmission-deferral applicaBon, 2nd life baReries can provide power support to a neighborhood grid transformer, when the energy demand is higher than the transformer’s capacity. 2nd life baReries charge during off-peak periods and are ready to inject the power back to the grid when needed. Second life baReries can also funcBon as electrical appliances for water and living-space heaBng, and as a reserve storage in the case of localized blackouts (Table 1). 2nd life baReries parBcipaBon in electricity supply in residenBal applicaBons is best uBlized for private usage, e.g. for common electricity.

(36) 36. management, to share locally produced green energy, or to reduce energy bills and environmental energy producBon and consumpBon impacts (Hossain et al., 2013; Van Troeye, 2019; Bobba et al., 2018; Casals et al., 2019).. In commercial applicaBons electricity demand is higher, thus the need for higher number of baReries is necessary. Second life baReries can be used in load following, i.e. aiding in balancing the generaBon of electricity and the load. AddiBonal commercial applicaBons for 2nd life baReries include acBng as reserve for localized blackouts and emergencies. Second life baReries can also replace, at least parBally, the much more expensive first life baReries in the applicaBons.. The power demand is the highest in industrial applicaBons, where 2nd life baReries can funcBon as storage and backup for RES, and in ancillary services, such as voltage support, frequency regulaBon and load following. 2nd life baReries can also have a significant part in maintaining uBliBes power reliability at lower cost, than what would be possible with new baRery storage units. (Hossain et al., 2013; Engel, H. et al., 2019; Palizban & Kauhaniemi, 2016)..

(37) 37. Table 1. The suitable applicaBons for Lithium-ion baReries (Palizban & Kauhaniemi, 2016).. In transport applicaBons, 2nd life baReries can be uBlized in EV charging staBons, for fast charging without overloading the local energy supply. They can even serve as distributed storage units for citywide tram networks. Although 2nd life baReries are not able to funcBon as well and reliably as a new baReries for everyday EV usage, the 70-80% capacity they possess can power a vehicle for short range mobility needs, e.g. for local traveling and commuBng, and powering city shuRles, school buses, fork lils, e-scooters and bikes, and even ferries. AddiBonally, second life baReries can be used to form a basis of vehicle leasing businesses, such as tax services, delivery firms etc. They can be uBlized for V2G applicaBons, and telecom base staBons and data centers as backup power sources (Hossain et al., 2013; Melin, 2018; Bobba et al., 2018; Casals et al., 2019)..

(38) 38. 2.7. Mobility as a Service (MaaS) Concerns over urbanizaBon and climate change, increased environmental awareness, and latest advancements in digitalizaBon, vehicle, internet, and informaBon communicaBon technologies, have affected strongly to transport and mobility markets. Mobility as a Service (MaaS) concept aims to transform the purely operaBonal transport model to comprehensive, sustainable and user focused mobility service assortment, resorBng to modern boRom-up approach instead of tradiBonal top to boRom. The objecBve is to provide all MaaS users an unbreakable mobility chain possibility, enabling one-step mobility within a MaaS’ region, i.e. a city (Yellowlees, 2017; Stopka et al., 2018).. The main objecBve of MaaS is to advance the energy efficiency and fluency of urban transport and mobility, prioriBzing constantly the end-users benefit. MaaS joins the public and business sectors with the users, striving to increase the aRracBveness of public transport and enhancing the operability of unbreakable mobility chains. It promotes cycling and walking as an alternaBve-choice of mobility to vehicle ownership. In addiBon, the development and uBlizing innovaBve mobility soluBons are part of MaaS, e.g. car sharing, and uBlizing EV fleets’ power supply potenBal in V2G soluBons and smart charging schemes. Furthermore, the concept can aid in traffic congesBon miBgaBon, and reduce the need for parking spaces, thus affecBng to urban aRracBveness and land use. Moreover, organizaBons can benefit from MaaS by being able to improve their logisBcal services more efficiently (The Finnish Government, 2016; The Ministry of Environment, Finland, 2017; Yellowlees, 2017; Stopka et al., 2018).. Successful and well-funcBoning Mobility as a Service does more than just develops transport and mobility. It has wide economic and environmental scopes. By enhancing the uBlizaBon of digitalizaBon and ICT, collaboraBon of its stakeholders, and dismantling unnecessary regulaBons and bureaucracy, MaaS improves the compaBbility of all different actors being part of its operaBng model. Hence, it aids new business models to break into markets, and improves the service environment. The main objecBve is to develop user friendly, market oriented and high quality mobility services, which oper-.

(39) 39. ate seamlessly as one economically and environmentally sustainable, digital and constantly evolving system. (The Finnish Government, 2016; The Ministry of Environment, Finland, 2017)..

(40) 40. 3. Horizon 2020 Lighthouse projects The European Union’s Horizon 2020 program includes several individual smart city projects, which are based on Lighthouse (LH) and follower ciBes (FC) concept. Each individual project is built around three Lighthouse ciBes and minimum of three follower ciBes, located in different EU states. The Lighthouse ciBes develop, test and demonstrate different integrated, innovaBve, and market-orientable soluBons in the fields of sustainability, smart energy and smart city soluBons. The LH ciBes act as role models for the follower ciBes, which are obligated to replicate the LH ciBes’ demonstraBons.. It is essenBal for each project’s success, that the demonstrated LH soluBons are replicable for the follower ciBes, either as an independent project, or on city district level. The follower ciBes are not expected to replicate every soluBon demonstrated by the LH ciBes. However, the variety of integrated soluBons is vast, and each city’s choice of selecBon depends on the city’s ambiBons, characterisBcs, geographical locaBon, technical level, resources, administraBon, culture, and set goals in sustainability and economic growth (European Commission, 2016 & 2017; Ferrer et al., 2017).. MaRers concerning a city’s capability to be accepted in a smart city project, and determining how advanced its smart city level is, depend on how advanced the city is in the following:. • State of Sustainable Energy and AcBon Plan (SEAP) • The level of smart grid soluBons in general • The uBlizaBon of RES • AdopBon of EVs and related technologies, i.e. innovaBve smart charging infrastructure • State of sustainable mobility and Mobility as a Service concept • UBlizaBon of 1st and 2nd life BESS • Sustainable buildings and construcBon soluBons • Level of state-of-the-art ICT soluBons (European Commission, 2016 & 2017; Ferrer at al., 2017).

(41) 41. A Lighthouse city’s goal is to achieve significant improvements in energy sufficiency, with encompassing uBlizaBon of various RES: wind, solar, hydro, wave, and geothermal energy, waste incinerated heat and energy storages. A LH city’s integrated electricity soluBons should be able to support the invocaBon of V2G, smart charging, and EV fleet soluBons. State-of-the-art ICT soluBons are vital for improved planning, management, control and maintenance of smart applicaBons and acBons. By guaranteeing successful implementaBon of robust ICT soluBons with smart energy and transport soluBons, physical urban infrastructure and operaBonal technologies in buildings, the adopBon of MaaS can be enhanced, and ciBzen/user engagement executed successfully (European Commission, 2016 & 2017; Ferrer at al., 2017).. The concept of Smart CiBes and CommuniBes (SCC) is a network of Horizon 2020 funded Smart City projects. The various projects may have different characterisBcs. However, they share a common goal: to achieve a sustainable, carbon neutral and environmentally friendly smart city operaBng model, driven by replicable smart energy innovaBons and technologies. Each Horizon 2020 smart city project has a duraBon of five years, in which it is required to gain results. That is to say, the FC ciBes are required to demonstrate smart city soluBons, and their follower ciBes are to replicate them or at least design a valid replicaBon plan to implement the smart city soluBons (European Commission, 2017).. The Horizon 2020 Smart CiBes network consists of the following smart city projects, with menBoned LH ciBes, number of follower ciBes, and project start dates:. • Atelie (Amsterdam & Bilbao, 6 FCs, 2019) • Poctyf (Alkmaa &, Evora, 6 FCs, 2019) • Sparcs (Espoo & Leipzig, 5 FCs, 2019) • CityXchange (Limerick & Trondheim, 5 FCs, 2018) • Making City (Groningen & Oulu, 6 FCs, 2018) • IRIS (Gothenburg, Nice Cote e d’Azur & Utrecht, 3 FCs, 2017) • MatchUP (Antalya & Dresden, 4 FCs, 2017) • Stardust (Pamplona, Tampere & Trento, 4 FCs, 2017).

(42) 42. • mySMARTlife (Hamburg, Helsinki & Nantes, 3 FCs, 2016) • Ruggedised (Glasgow, RoRerdam & Umeå, 3 FCs, 2016) • GrowSmarter (Barcelona, Cologne & Stockholm, 5 FCs, 2015) • Remourban (No}ngham, Tepebasi/Eskisehir & Valladolid, 2 FCs, 2015) • Replicate (Bristol, Florence & San SebasBan, 3 FCs, 2015) • Sharing CiBes (Lisbon, London & Milan, 3 FCs, 2015) • SmartEnCity (Tartu, Souderborg & Vitoria-Gasteiz, 2 FCs, 2015) • Smarter Together (Lyon, Munich & Vienna, 3 FCs, 2015) • Triangulum (Eindhoven, Manchester, Stavanger, 3 FCs, 2015) (EU Smart CiBes InformaBon System, 2020). For each parBcipaBng city, it is essenBal that the planning of smart ciBes’ infrastructures and processes can be integrated seamlessly with related exisBng naBonal policies and regulaBons. FuncBoning and successful business models, as well as finance and procurement processes are important for a smart city projects advancement and success. AcBve engagement of ciBzens and key stakeholders enhances wider perspecBve planning and more thorough decision-making processes. The district level integraBon of smart homes and buildings, use of RES, smart mobility and energy storage soluBons, and exploiBng smart management systems with integraBon of reliable ICT soluBons, resonate a strong posiBve example for other city districts to follow. The end-result is more sustainable, energy efficient and holisBc smart city development, which can be imitated by ciBes not yet part of the SCC (The IRIS Smart CiBes ConsorBum, 2017; Massink, 2019)..